code: def csrmask(gidxA, A_weights, gidxB):
      @tf.custom_gradient
      def _lambda(A_weights):
          return csrmask_real(gidxA, A_weights, gidxB)
  
      return _lambda(A_weights)
  
imports: import numpy
  import tensorflow
  from ..._sparse_ops import _bwd_segment_cmp, _csrmask, _csrmm, _csrsum, _gsddmm, _gspmm, _scatter_add, _segment_reduce
  from ...base import ALL, is_all
  from ...heterograph_index import create_unitgraph_from_csr
  from .tensor import asnumpy, context, copy_to, tensor, zerocopy_from_numpy
label_desc: Use image node_id 23 for calling a global function with example usage: csrmask(gidxA, A_weights, gidxB) and returns: _lambda, csrmask_real